Method of production, apparatus and system

ABSTRACT

There is provided a method of regulating the formulation of a multi-component product comprising a product attribute profile, the method comprising providing a first and second component of the product, each component having a component attribute profile; supplying to a product formulation zone the first component and the second component in a desired ratio and combining the first and second components together to provide the product or a precursor thereof to yield a target product attribute profile; responsive to a change or predicted change in at least one component attribute profile, supplying information concerning the attribute change to a data processing apparatus and calculating with respect to that change an adjustment in the ratio to reduce the deviation of one or more attributes of the product attribute profile from the target product attribute profile. A production system is also provided.

The present invention generally relates to a method of producing, andapparatus and system for producing, a product. In particular, but notexclusively, the present invention relates to regulating a productattribute profile of a multi-component product.

A product intended for sale is generally produced each year in vastquantities to satisfy consumer demand, where the consumer may be thegeneral public or a business enterprise. Traditionally, productmanufacturers have relied on sales made in previous years to estimatethe levels necessary for the upcoming year. However, guesstimating oremploying “rules of thumb” carry the risk of manufacturing tosignificantly offset or out of date targets. Further, such techniques donot necessarily allow the manufacturing process to be optimised in termsof utilising the raw materials to their fullest extent or in terms ofmaintaining a product having consistent component attribute profiles,for example taste, shelf life and costs, despite variances in the supplyof the components of the product.

Products often contain a plurality of different components; for examplesandwich filler may be constituted by a variety of different types ofcomponents—the composition determining the overall taste, texture andother properties of the resulting sandwich filler and consequently thesandwich. It, therefore, remains an important aspect of productproduction to maintain the properties of the product components to theextent that a consumer would fail to recognise a difference in the finalproduct.

Consumer demand and price sensitivity are also important aspects toconsider in product production. The volume of a product produced shouldbe sufficient to meet consumer demand at a price consumers will bear.

Some of the problems and issues associated with existing and knownproduct production methods may be due to the small number (three tofour) of local experts in a given field making important decisions,which decisions can on occasion be conservative and be based on highlevels of assumption and uncertainty. The experts may rely on experienceand a rule of thumb which the reader will acknowledge may not always bean accurate way to apply processes consistently. Such techniques andprocedures are often restricted in terms of the low level of criticaldata that is able to be shared among decision making parties.

It is desirable, therefore, to provide a mechanism to link consumerdemand with manufacturing supply, while enhancing the efficiency of theproduction process so that waste of raw material is minimised andproduct attribute profile consistency is regulated and maintained.

According to a first aspect, the present invention encompasses a methodof producing a multi-component product comprising a product attributeprofile, the method comprising providing a first and second component ofthe product, each component having a component attribute profile;supplying to a product formulation zone the first component and thesecond component in desired amounts and combining the first and secondcomponents together to provide the product or a precursor thereof toyield a target product attribute profile; responsive to a change orpredicted change in at least one component attribute profile, supplyinginformation concerning the attribute change to a data processingapparatus and calculating with respect to that change an adjustment inthe amounts to reduce the deviation of one or more attributes of theproduct attribute profile from the target product attribute profile.

The attribute profile of the product may be considered to be theintrinsic characteristics of the product. The attribute profile relatesto the properties of the product. Similarly, the component attributeprofile relates to characteristics and properties of the component ofthe product. For example, the age of the product may be regarded asquantifiable attribute data. Of course, quantifiable attribute data maybe constituted by other information relating to the product.

The product attribute profile or the at least one component attributeprofile may be selected from the cost of freight and storage of aparticular component, cost of a particular component, quality of aparticular component, consumer demand of a particular component,available supply of a particular component and cost ofprocessing/blending. For example, when the freight and storage cost of aparticular component is high, it may be preferred to resort to analternative component that exhibits, for instance, similar or identicalcharacteristics to the original component, but has lower associatedcosts. The cost of the overall process can in this way be reduced,thereby optimising the way in which a product is produced. Similarly,when the quality or available supply of a particular component isnegatively affected or is predicted to be negatively affected in thefuture, for instance, the method involves the step of adjusting theratio or amounts of the components to counteract such a change orpredicted change so as to reduce the deviation of the product attributeprofile from an existing or target product attribute profile.

It is desirable for the physical properties of the product to beregulated and this can be achieved by supplying information concerningany attribute profile change or anticipated change to the system, forinstance to a database, and then calculating how to minimise or reducethe change. In some circumstances, it may not be possible to replace alike component with a like component; in which case, a replacementcomponent can be selected which most closely matches the necessaryattribute(s) of the component to be replaced.

A component of the product may be considered a particular type ofconstituent of the product. Where the product is sandwich filler, forexample, it may include a component such as chicken originating from aparticular source. In other cases, it may be the same type ofconstituent but having different properties; for instance, chicken takenfrom two different regions and having different attributes profiles suchas taste and availability.

An attribute of a component may fluctuate over time by increasing ordecreasing. For example, where the attribute is the cost of a particularcomponent, the cost may increase or decrease depending on variouscontributing factors such as season, availability and demand.

The target product attribute profile may be understood as the attributeprofile that is desirable. It may be considered as the attribute profilethat is “ideal” in terms of initial values. The optimal combination canbe obtained by setting constraints in the system so as to arrive at thedesired product attribute profile. There may be varying degrees ofacceptability of the deviation from the target product attributeprofile; this may, for example, be in the region of +/−5% of the targetproduct attribute profile value(s).

It will be appreciated that the adjustment in the ratio of componentsmay be “zero”. For instance, a product may consist of initial componentsX, Y and Z. An adjustment may be calculated such that initial componentX of the product is replaced with a similar, but not identical,component Q having a very similar attribute profile to initial componentX. However, the ratio between the components of the product may notchange in that component X may be replaced with component Q in identicalamounts, so that the ratio of components X, Y and Z is the same ratio asthat of components Q, Y and Z. In such a case, the ratio change would becalculated as “zero”; however, the product has still been adjusted inthe sense that the components of the product have been exchanged withthe intention of maintaining a consistent product attribute profile.

The information acquired on the at least one component attribute profilemay involve consumer intelligence gathered via sensory attributes. Bothchemical and physical attributes may be measured.

One or more embodiments address the problem of how to maximise thequality of a product with the currently available supply of components.It is desirable to replace a component or change the blend ratio withoutdetriment to the quality and taste of the product. One or moreembodiments enables long-term planning solutions and flexibility toconsider new sources and suppliers of components while maintaining theconsistency of the product. This may be by virtue of forecasted futurecrop attributes, for example.

It will be readily apparent to the reader that many other attributes arealso applicable which are encompassed by the embodiments describedherein and variants thereof.

In one or more embodiments, the raw material and physicalcharacteristics, costs and other attributes may be input into revenueanalytics software, which may process the information and provide apredictive modelling score. This score may be used to optimise theprocess by purchasing raw materials that have identifiable measureableattributes. The raw materials thus purchased may be recorded and theircorresponding measured component attribute profiles may be fed into adatabase. Various calculations can be made based on various potentialscenarios, and the materials may then be selected/combined based on thetarget product attribute profile; for example a product having a certainquality or particular cost.

The component attribute profiles may be manually input into a databaseor this may be an automated procedure. The database may be in the formof a spreadsheet which stores the information.

Rather than important decisions in the production of products being madeby a small number of experts, one or more embodiments in accordance withthe present method enables a cross-functional decision making processwith general managers included in key decisions. To this end, robustplanning can be executed at a very detailed level based on data-drivendecisions. There is also enhanced visibility such that critical data iscommon among relevant parties so that appropriate and informed decisionscan be made.

It is often the case that major decisions can be based on experience,but the minor decisions do not always follow this rule and less thanoptimum decisions can, therefore, be made. As an example, it may be thecase that 95% of components of a product are utilised in the mostefficient manner, but the remaining 5% may be unusable due toguesstimation. One or more embodiments of the present method allowoptimisation in the sense that substantially the final 5% would also beutilised in the most efficient manner owing to information supplied tothe database on component attributes and anticipated componentattributes. As a result, there is provided a decision supportcapability.

One or more embodiments in accordance with the method enablesinfrastructure planning to the effect that an attribute change of acomponent is recognised quickly or is predicted in advance of suchchange, so that it becomes possible to manage the logistics of theoperation more efficiently compared with having to react to suddenchanges, such as a realisation that a particular component is no longeravailable. By contrast, one or more embodiments in accordance with thepresent method recognises that there may be a shortage in supply ofparticular component and adjust the ratio of the components to accountfor this change without necessitating an entirely new product—insteadthe components of the product may be substituted with those that mostclosely resemble the attribute profiles of the initial components,thereby maintaining as much as possible the overall product attributeprofile. In another example, the information may provide for an increasein supply of a component and arrangements may then be made in advancefor additional storage capacity of the product.

The attribute profile of availability of a particular component orsupply thereof may be influenced by a variety of factors, includingseasonal variations in growth, natural disasters, a change inimportation/export duties and changes in transport of the component.

One or more embodiments in accordance with the method thus provide a wayin which to regulate the attributes of a product. One or moreembodiments in accordance with the method rely on information suppliedto the database, which information may be considered more reliable thantraditional demand forecasting because the information is acquired froma direct source in the form of the consumers that will eventuallypurchase the end product, rather than information based purely onprevious year(s) sales figures, which can be misleading.

Supply of components can in this way be linked to consumer demand toenable quicker and more precise decisions, while optimisingprofitability and growth. It could be said that the method synchronisesand optimises decisions involving the initial product components to thefinal product. In this way, the correct product may be offered to thecorrect consumer at the correct time for a correct amount. Correct maybe understood as meaning suitable.

One or more embodiments in accordance with the method allow theattributes of a multi-component product to be optimised such that rawmaterial waste is minimised. Raw materials which may constitute thecomponents of the product, for instance chicken used to make theproduct, can be selected in the correct quantities by way of the presentmethod, thereby reducing waste. The correct quantities can beestablished, for example, from the information acquired from theconsumers together with any predictions relating to componentavailability.

The product may include components from at least two different sources.This may include, for example, the same type of chicken taken fromdifferent locations. Of course, in some cases, the source may be in thesame geographical location for all components, but the components mayoriginate from different types of product, such as different type ofchicken (standard or free range).

The first and second components may reside in separate vessels beforebeing combined. Regulation of the attribute profile of the product maybe enhanced by keeping the components separate before combining. Thestep of adjusting the ratio or amounts of the components is made easierby keeping the components separate so that appropriate amounts ofcomponents can be selected when required.

The vessels may include valves for allowing controlled passage of thecomponents to the product combination zone. The components may then becombined in the desired ratios in a controlled manner to provide anaccurate product composition.

The method may further comprise automatically adjusting said ratio toreduce said deviation.

The adjustment in the ratio may comprise replacing said first componentor said second component with a third component having an attributeprofile in a desired ratio to yield said target product attributeprofile.

The method may further comprise automatically recognising theavailability of said third component and calculating said adjustment independence on said availability.

The product may include components from at least two different sources.

The adjustment in the ratio to reduce the deviation of one or moreattributes of the attribute profile from the target attribute profilemay be calculated with respect to a selected period of time. Theselected period of time may be the longest possible period of time, aperiod of time between the present and subsequent change, a season ofthe year or any other time period.

The method may include the step of marketing and promoting the producttin response to sufficient existing and anticipated stock levels of thejuice.

The method may be a computer implemented method and the calculating stepmay be executed by a data processor.

The attribute of at least one component of the product may fluctuateover time.

One or more embodiments in accordance with the present invention thusallow the modelling of product component attributes by representingtheir properties and characteristics in data form.

There are various ways the component information may be utilised. Forexample, the data for a particular product may be input to a centraldatabase. The data may form an optimisation plan or framework forproducing a product from known available components. The variousparameters may be continuously updated. In this way, the optimisation ofthe method occurs by using the existing data and combining it with thenew data/information so that a new or modified optimisation plan can begenerated. In such an example, the method allows the user to build on aprevious model or models, rather than relying on a completely new modeleach time. Optionally, a user may input data for a particular plan eachtime there is a change or expected change in requirements for theproduct to be produced or of the components of the product.

Another way of optimising may include inputting all the information intoa database. Then, in the event of a new scenario, the optimisationmodule may review the information received and acquire any missing data(in terms of previously known data) from the database before running theoptimisation sequence.

The data or information on component attributes should be viewed notsimply as data, but a representation of the physical components andproduct, and by representing the product components and product in termsof their key attributes, it is possible to model a simulation foroptimising a product combination made from several product components.

So far as the taste attributes are concerned, the optimisation of thecombined product can thus be seen as the optimisation of the physicalsensation experienced by the consumer when consuming the combinedproduct, the optimisation taking place in an electrical or virtualenvironment. Furthermore, other physical aspects such as availability ofcomponent products may also be taken into account.

Viewed from a hierarchical perspective, the combination falls within anobjective constraint, such as cost per unit volume to manufacture or tothe consumer.

The constraints and attributes may be considered simultaneously, forexample.

There is also generally a quality constraint which is a function of asubset of the attributes, for example taste attributes.

Additionally, a constraint may be viewed as a bound on an attribute or afunction of one or more attributes.

In accordance with an embodiment of the present invention, the method isdirected towards regulating the formulation of a product having a targetproduct attribute profile. The attribute profile may be viewed as aconstraint in the formulation optimisation model. Optionally, the targetproduct attribute profile may be subject to an overriding constraintsuch as total cost of the product comibination.

The constraint or constraints may include quality and component boundconstraints which enforce the quality and component bounds for finishedproducts. Other constraints may include supply and demand constraintsinvolving sourcing of raw materials. Additionally, capacity constraintsmay also play a factor in determining the optimisation model of aproduct; i.e how much of a product may be produced and stored for anadequate period before sale. In this way, logistical constraints are animportant consideration for the optimisation model.

The adjustment in the ratio or amounts to reduce the deviation of one ormore attributes of the product attribute profile from the target productattribute profile may be calculated with respect to a selected period oftime. The attribute profile of a component may change over time;similarly, the attribute profile of a product may change over time.Hence, where the product is a vegetable for example, it is possible thatthe attribute profile of a particular component changes by season. Morespecifically, the price of the vegetable may vary from season to season,and adjustments to the ratio or blend of the product may be necessary,for instance, to keep the cost of the product within an acceptable rangeor below a certain threshold or to keep the other vegetable attributessuch as its taste consistent over the different seasons. Suchadjustments may involve replacing component(s) entirely or modifying theratios/amounts of the existing components.

The selected period of time may be the longest possible period of time,a period of time between the present and subsequent change, a season ofthe year or any other time period that may be appropriate for thedesired yield.

One or more embodiments in accordance with the method may include thestep of marketing and promoting the product in response to sufficientexisting and anticipated stock levels of the product. There is a directlink between supply and consumer demand. During periods where supply ofa particular component is short or expected to be short, for instance,it may be prudent to refrain from marketing or promoting the productsince its supply will be affected and it may not in such circumstancesbe possible to meet the demands of the consumers. Conversely, when theacquired information on component attributes shows that supply will bereadily available, it may be beneficial to market and promote theproduct thereby increasing potential sale of the product, which increasein sale can be readily met by virtue of the increased availability ofcomponents.

In one or more embodiments, the method may be a computer implementedmethod and the calculating step executed by a data processor.

There are various ways the method allows the component information to beutilised. For example, the data is inputted to a central database wherevarious parameters are continuously updated. In this way, theoptimisation of the method occurs by using the existing data andcombining it with the new data/information so that a new optimisationplan can be generated. The method, therefore, allows the user to buildon previous model, rather than relying on a completely new model eachtime.

Another way of optimising may include inputting all the information intoa database. Then, in the event of a new scenario, the optimisationmodule may review the information received and acquire any missing data(in terms of previously known data) from the database before running theoptimisation sequence.

The data or information on component attributes is not simply data, buta representation of the physical attributes of the product, and byrepresenting the product in terms of its key physical attributes, itbecomes possible to model a simulation to optimise a combination madefrom several components.

The method may be a computer implemented method and the calculating stepmay be executed by a data processor.

According to a second aspect, the present invention provides a systemfor producing a multi-component product comprising a product attributeprofile, the system comprising means for storing a first and secondcomponent of the product, a product formulation zone for combining thefirst and second component of the product in desired amounts effectiveto yield a target product attribute profile, the first and secondcomponent each having a component attribute profile, wherein the systemcomprises a data processing apparatus operable to receive informationconcerning a change or predicted change in at least one componentattribute profile and, in response thereto, is operable to calculatewith respect to that change an adjustment in the amounts to reduce thedeviation of one or more attributes of the product attribute profilefrom the target product attribute profile.

The means for storing the first and second components may compriseseparate vessels in the system.

The formulation zone may comprise a combination chamber in the system.The size of the combination chamber may be dependent on the intendedproduction size and rate of the product.

According to a third aspect, the present invention provides a computerimplementable method of modelling the production of a multi-componentproduct comprising: representing said multi-component product by datavalues indicative of a physical attribute profile of saidmulti-component product; representing first and second components ofsaid multi-component product by data values indicative of respectivephysical attributes of said first and second components; and deriving acombinatorial relationship between respective data values of saidphysical attributes of said first and second component to yield acombined attribute profile within predetermined limits of data values ofsaid multi-component product attribute profile.

Representing physical attributes or characteristics, for exampleattributes of a product contributing to a taste sensation as datavalues, allows the production and formulation of products to be modelledand simulated in an electric or virtual environment. Thus, naturalresources such as products need not be wasted in trying out formulationsor manufacturing consistency.

The attributes may be taste sensation attributes.

The method may further comprise applying a constraint to deriving saidcombinatorial relationship.

The constraint may comprise a data value or range of data valuesrepresentative of the cost of said multi-component product.

The constraint may comprise a further data value or range of data valuesrepresentative of an available amount of said first and/or secondcomponents.

The constraint may comprise a yet further data value or range of datavalues representative of an amount of multi-component product to beproduced.

The combinational relationship may comprise a ratio of said firstcomponent to said second component.

The method may further comprise providing control parameters derivedfrom said combined attribute profile to a multi-component productionsystem for controlling the supply of said first and second component toa formulation zone in amounts corresponding to said combinatorialrelationship for combining to form said multi-component product.

There is also provided a computer program comprising computer programelements operative in data processing apparatus to implement the methoddefined herein.

According to a fourth aspect of the present invention, there iscontemplated the use of the system such as set out above and accordingto any of the appended system claims in regulating a multi-componentproduct attribute profile.

Various embodiments of the present invention will now be described moreparticularly, by way of example only, with reference to the accompanyingFigures; in which:

FIG. 1 is a schematic representation of a system for the production of amulti-component product in accordance with an embodiment of the presentinvention;

FIG. 2 is a block diagram illustrating the components of a dataprocessing apparatus;

FIG. 3 is a schematic overall process flow diagram illustrating a systemregulating the formulation of a multi-component product having a productattribute profile;

FIG. 4 is a flow diagram of the optimisation procedure in accordancewith an embodiment of the present invention;

FIG. 5 is an illustration of an input interface display screen inaccordance with an embodiment of the present invention;

FIG. 6 is an illustration of an output interface display screen inaccordance with an embodiment of the present invention;

FIG. 7 is a schematic representation of a system for the production of amulti-component product in accordance with an alternative embodiment ofthe present invention;

FIG. 8 is a diagram of a two dimensional linear integer program; and

FIG. 9 is a graphical representation of an interior point method model.

Referring first to FIG. 1, there is illustrated a schematic diagram of asystem for the production of a multi-component product having a productattribute profile. The system is generally indicated 1.

The system 1 comprises a database 27 for storing information 25concerning consumer preferences in terms of the measurable properties orattributes of the components. The information 25 also includesconstraints including supply, demand and cost of particular components.The system 1 also comprises three product component vessels 3, 5 and 7,which feed into a formulation zone constituted by a combination chamber9. The vessels 3, 5 and 7 and combination chamber 9 are provided withmonitoring devices 11, 13, 15 and 17 respectively. Each vessel 3, 5 and7 is also provided with a valve 19, 21 and 23, respectively forcontrolling the flow of respective components to the combination chamber9.

In the described embodiment, the product component vessels 3, 5 and 7and the combination chamber 9 are cylindrical in shape, which aidscombining and flow therethrough.

The monitoring devices 11, 13, 15 and 17 monitor the properties of theproduct components and product formulation in respective vessels 3, 5and 7 and combination chamber 9 and supply this information to thedatabase 27 via the control unit 29. In this embodiment, vessel 3contains sweet corn, vessel 5 contains tuna A and vessel 7 contains tunaB. Measurable properties or attributes of the respective components andthe sandwich filler include for example the texture and viscosity, tunaconcentration and acidity may be monitored. The monitoring devices 11,13, 15 and 17 include, either integrally or remotely, analyticalapparatus for performing High Performance Liquid Chromatography and GasChromatography (not shown).

The information corresponding to the properties or attributes representsa particular component, such as a sandwich filler component or sandwichfiller product. In this way, a physical combination may be representedby a formulation having data values representative of physicalproperties. Further attributes could also be monitored or derived suchas the volume of product present, its temperature thereby delimiting theproduct in further detail. Representing physical substances as datavalues allows the modelling of the substance in data processingapparatus.

Information 25 acquired on consumer preferences, including tasteattributes of preferred tuna content, sweet corn content and texture aresupplied to the database 27. Control unit 29 may include data processingapparatus 28 such as schematically illustrated in FIG. 2. Here, there isshown a schematic and simplified representation of an illustrativeimplementation of a data processing apparatus 28 in the form of acomputer system. As shown in FIG. 2, the computer system comprisesvarious data processing resources such as a processor (CPU) 40 coupledto a bus structure 42. Also connected to the bus structure 42 arefurther data processing resources such as read only memory 44 and randomaccess memory 46. A display adapter 48 connects a display device 50,having a display screen 52, to the bus structure 42.

One or more user-input device adapters 54 connect the user-inputdevices, including the keyboard 56 and mouse 58 to the bus structure 42.An adapter 60 for the connection of a printer 72 is also provided. Amedia drive adapter 62 is provided for connecting the media drives,including the optical disk drive 64, the floppy disk drive 66 and harddisk drive 68, to the bus structure 42. A network interface 70 isprovided thereby providing processing resource interface means forconnecting the computer system to one or more networks or to othercomputer systems. The network interface 70 could include a local areanetwork adapter, a modem and/or ISDN terminal adapter, or serial orparallel port adapter etc, as required. In this embodiment, the networkinterface 70 is in communication with the database 27 of FIG. 1.

It will be appreciated that FIG. 2 is a schematic representation of onepossible implementation of a computer system. It will be appreciated,from the following description of embodiments of the present invention,that the computer system in which the invention could be implemented maytake many forms. For example, rather than the computer system comprisinga display device 50 and printer 72, it may be merely necessary for thecomputer system to comprise a processing unit, and be accessible toother computer systems.

A CD-ROM 74 and a floppy disk 76 are also illustrated. A computerprogram involving an algorithm for implementing various functions orconveying information can be supplied on media such as one or moreCD-ROMs 74 and/or floppy disks 76 and then stored on a hard disk 68, forexample. A program implementable by the computer system may also besupplied on a telecommunications medium, for example over atelecommunications network and/or the Internet, and embodied as anelectronic signal.

The data processor 28 is configured to access consumer preferenceinformation 25 and generate an electronic representation of a desiredcombination formulation as data values of a target product attributeprofile based on the consumer preferences. The target product attributeprofile is an “ideal” profile in that it is generated, in thisembodiment, without considering constraints such as cost andavailability of component products. Thus, the target product attributeprofile is an attribute profile of the product which possesses thedesirable characteristics based on consumer preference information 25—inthis case, the desired properties of the product combination that willdetermine its taste and mouth sensation. The target product attributeprofile may be viewed as a product quality index and typically eachattribute may have a range of values.

The data processor 28 is further configured to deduce the ratio ofproduct components (e.g ratio of tuna to sweet corn content) necessaryto achieve a filler having an attribute profile satisfying the targetattribute profile. For example, the user can provide multiple productcomponents, each containing unique attributes, usage limitations (e.g.,component availability and timing) and costs. The data processor 28 willsimultaneously consider all of these factors in determining how to matcheach component to meet or exceed the target attribute profile for theentire production period whilst minimizing cost.

Thus, formulating a product blend may be controlled automaticallyfollowing deduction of the product component ratios or amounts forsatisfying the target attribute profile. Optionally, parametersrepresenting the ratio or amounts may be displayed to a user on adisplay screen 52 and control unit 29 configured with those parametersby a user. The ratio can be input to the control unit 29, which in turnoperates valves 19 and 21 to supply product components in the desiredratio to the inlet 33 of combination chamber 9 conduits 31. Combiningoccurs in the combination chamber 9 on the principles of a continuousflow reactor. The amount of the tuna A and sweet corn in the filler canbe controlled in real-time by adjusting the flow of the components tothe combination chamber 9 based on readings from the monitoring device17 fed back to control unit 29. The components are combined to yield aformulation satisfying the target product attribute profile.

In this and other embodiments, information 25 may include more thaninformation concerning consumer preferences; for example, estimatedproduct sales based on product component attributes, product componentavailability and cost per component of the product. This information maybe continually updated and input to the database 27. The control unit 29also receives current information on the attribute profile of eachcomponent from the monitoring devices 11, 13, 15 (before combining hasoccurred). The control unit 29 also receives current information on theattribute profile of the formulated product from the monitoring device17 (after combining has occurred). The status of the attribute profilesof the components and the product combination are, therefore, known byway of the monitoring devices 11, 13, 15 and 17. In an optionalembodiment, the updated attribute profile status is input to dataprocessing apparatus 28 which is configured to be responsive to theupdated status to deduce an updated component ratio and forward theratio to control unit 29. The control unit 29 then sends control signalsto the relevant valves 19, 21 and/or 23 to adjust the flow of componentsto the combination chamber 9.

Following a change or predicted change (based on acquired information25) in a component attribute profile, for example the reducedavailability of tuna A, the change is included in information 25 andsupplied to the database 27. The data processor 28 accesses theinformation 25 in the database 27 and establishes whether the change orpredicted change will result in an unacceptable deviation from thetarget product attribute profile. If such a deviation is identified, thedata processor 28 deduces how best to counteract the deviation bygenerating an updated component ratio which more closely yields thetarget product attribute profile.

The data processor 28 can establish that a deviation is likely to occurdue to the reduced availability of sugar. In this particular case, thedata processor algorithm generates a solution to this problem; moreparticularly an adjusted ratio/combination of the components which wouldminimise the deviation owing to the reduced availability of tuna A. Inthis embodiment, the data processor 28 calculates that the tuna A ofvessel 5 can be replaced by tuna B due to similar component attributes,whereby to minimise the deviation of the target and current productattribute profiles.

Using the calculated adjustment, an operator can manipulate the controlunit 29 to make said adjustment to the combination of the formulation incombination chamber 9 by closing valve 21, belonging to vessel 5, andopening valve 23, belonging to vessel 7. The adjustment is made byeffectively replacing tuna A with tuna B. Of course, in otherembodiments, a component may not be entirely replaced; instead theamount supplied of a particular component may change. Optionally, theadjustment may be made automatically in that updated control parametersto modify the product component ratio/amount input to the combinationchamber 9 are sent to the control unit 29. The control unit 29 may thensend control signals to valves 19, 21 and 23 to adjust the flow ofcomponents to incorporate tuna B from vessel 7.

Following said adjustments, filler from sweet corn and tuna B may beextracted from the combination chamber 9 by way of the outlet 35.

Referring back to FIG. 2, the memory resources, typically RAM 46 and HDD68 comprise information on the various components of the product; in thepresent example, these components include: component i (sweet corn)having component attribute A, component j (tuna A) having componentattribute B, and component k (tuna B) having component attribute C.These memory resources of the produced product, i.e the customerpreferences, also contain the system constraints in terms of qualityconstraints including taste attributes, and operational constraintsincluding minimum supplier purchases, load-out constraints, end-supplyrequirements, combining/blending constraints, pasteurizing capacity andsafety stock limit.

The memory resources also store computer elements, typically in the formof instructions and parameters, for configuring data processingapparatus 28 to retrieve data from database 27, process the data todeduce the ratios of product components to combine in the combinationchamber 9, and also to receive real-time attribute data from the system1 to utilise in deducing the ratios/amounts of product components forachieving the target attribute profile of the combined product.

Among the computer program elements there is included an optimisationmodule, an input interface template and output interface templatemodule.

It will be appreciated that although the embodiment of FIG. 1 relates tofood, in other embodiments the product may be non-food related such as aconcrete mixture, for example. The concrete mixture may includecomponents such as cement and sand mixed in the appropriate proportions.Adjustment could be made to the components of the concrete mixture onthe same principles as described in relation to FIG. 1.

The overall process flow of a system regulating the formulation of amulti-component product attribute profile implementing an embodiment ofthe present invention will now be described with reference to FIG. 3.

The overall process begins with the preference information 80 initiallyproviding sensory research 80 a and volume forecast data 80 a on theproduct to be produced. An analysis is made of the volume 81 andattribute requirements 82 of the product components depending on volumeand attribute availability. For example, if the resources of tuna werelimited in terms of availability, it may be prudent to allocate thelimited resource to a particular market to achieve the optimal scenario.This may, for example, involve allocating to a particular market orproduction region to maximise quality of product or overall profits. Anoptimisation and combination plan is formulated 84. The product iscombined, adjusted if necessary, stored and transported 85, whichresults in a final product 86 issued to the consumer.

Referring to FIG. 4, there is illustrated a flow diagram of theoptimisation procedure implemented by the data processing apparatus 28in accordance with an embodiment of the present invention.

At step 500, a user uploads acquired component attributeinformation/data and input optimisation plan parameters into the system;for example by manually inputting it. The data is saved into a database505 which may be implemented on HDD 68 or a remote memory store as shownat step 503. Visual Basic Application (VBA) modules validate the user'sinput data against validation criteria set in the VBA modules. Anexample of an input interface display screen is shown in FIG. 5. Theinput interface provides data input fields for the quality bounds of thetaste factors. The Quantity of available tuna A and tuna B is alsoindicated in respective fields.

The component or ratio bounds are also controlled from this inputdisplay. The user can adjust the ratio of combining components in orderto control taste or to meet operational and/or supply constraintsinherent in supplying each combination component. For example, onecombination component may need to be used in a specific time period.Therefore, the user can control the specific component usage rate tosatisfy the operational constraint while meeting taste targets. Thequantity of available tuna A and B required at a particular time is alsoindicated in respective fields. This requirement ensures an appropriateamount of safety stock is available to meet taste and supply targets.Additionally, this interface provides the ability to input the start andend date of the analysis period, as well as record comments and trackpreviously executed combination plans over time (Plan ID and RevisionID).

The VBA modules run an optimisation sequence at step 507 by accessingthe information in the database 505. The optimisation sequence may beimplemented using any suitable optimisation routine such as the interiorpoint methods (see FIGS. 7 and 8 for more detail). For example, thesystem of linear equations can be solved using Cplex optimizing softwareavailable from International Business Machines Inc™, Armonk, N.Y. Arange of possible solutions can be produced. The possible solutionsrepresent the combination plans that define the inputs to use, resourcesto use and products to be made. The routine generates outputoptimisation combination parameters at step 509. The generatedparameters are relayed back to the database 505. The VBA modules readthe data from the database and then display this information on anoutput display screen as indicated at step 511. An example of the outputdisplay screen is illustrated in FIG. 6, which shows the associatedcosts which each of the combinations of different component ratios andamounts having their corresponding attribute values.

From this display of optimised combination parameters, a user may selecta desired product combination for a given period. The quantity, orratio, of each component, for each time period, is the optimal productcombination plan which represents the user defined target attributetaste profile. These quantities are used to generate purchase decisionsand implement the combination plan to meet consumer demand. Theparameters for the selected product combination plan may be inputautomatically to the control unit 29 or manually input.

The database 500 is also continuously monitored, at step 513. When thedatabase monitor detects a newly uploaded optimisation plan, itautomatically initiates the optimisation sequence at step 507 so as togenerate new optimisation combination parameters at step 509. Hence, forexample, if the optimisation plan parameters change in that theavailability of a particular component becomes scarce, this informationwill be saved to the database 505, and the new optimisation parametersmay then be calculated on that basis. From the updated optimisationparameters, the user or operator may adjust the control unit 29 settingsso as to produce a product in accordance with the new optimisedcombination parameters, and/or the new parameters may automatically beinput to the control unit 29.

Referring now to FIG. 7, there is shown a schematic representation of asystem for the production of a multi-component product, having a productattribute profile, in accordance with an alternative embodiment of thepresent invention. The system is generally indicated 701.

The system 701 is similar to that shown in FIG. 1.

The system 701 comprises a database 727 for storing information 725concerning consumer preferences in terms of the measurable properties orattributes of the components. The information 725 also includesconstraints including supply, demand and cost of particular components.The system 701 also comprises three product component vessels 703, 705and 707, which feed into a formulation zone constituted by a conveyorbelt 709. The vessels 703, 705 and 707 and conveyor belt 709 areprovided with monitoring devices 711, 713, 715 and 717 respectively.Each vessel 713, 715 and 717 is also provided with a dispenser 719, 721and 723, respectively for controlling the flow of respective componentsto the conveyor belt 709.

The monitoring devices 711, 713, 715 and 717 monitor the properties ofthe product components and final product in respective vessels 703, 705and 707 and conveyor belt 9 and supply this information to the database727 via the control unit 729. In this embodiment, vessel 703 containschicken, vessel 705 contains vegetables A and vessel 707 containsvegetables B. Measurable properties or attributes of the respectivecomponents and the product (pie) include for example the quality andcomponent concentrations may be monitored. The monitoring devices 711,713, 715 and 717 include, either integrally or remotely, analyticalapparatus for performing High Performance Liquid Chromatography and GasChromatography (not shown).

Information 725 acquired on consumer preferences, including tasteattributes of preferred chicken content, vegetable content and textureare supplied to the database 727. Control unit 729 may include dataprocessing apparatus 728 such as schematically illustrated in FIG. 2.Here, there is shown a schematic and simplified representation of anillustrative implementation of a data processing apparatus 728 in theform of a computer system.

The data processing apparatus 728 is further configured to deduce theratio of product components (e.g ratio of chicken to vegetables content)necessary to achieve a pie product having an attribute profilesatisfying the target attribute profile. Thus, formulating a product maybe controlled automatically following deduction of the product componentratios or amounts for satisfying the target attribute profile.Optionally, parameters representing the ratio or amounts may bedisplayed to a user on a display screen 52 and control unit 729configured with those parameters by a user. The ratio can be input tothe control unit 729, which in turn operates dispensers 719 and 721 todispense product components in the desired ratio to the pie pastry 724of conveyor belt 709. Combining occurs on the conveyor belt 709. Theamount of the vegetables A and chicken in the pie can be controlled inreal-time by adjusting the flow of the components to the conveyor belt709 based on readings from the monitoring device 717 fed back to controlunit 729. The components are combined to yield a formulation satisfyingthe target product attribute profile.

In this and other embodiments, information 725 may include more thaninformation concerning consumer preferences; for example, estimatedproduct sales based on product component attributes, product componentavailability and cost per component of the product. This information maybe continually updated and input to the database 727. The control unit729 also receives current information on the attribute profile of eachcomponent from the monitoring devices 711, 713, 715 (before combininghas occurred). The control unit 729 also receives current information onthe attribute profile of the formulated product from the monitoringdevice 717 (after combining has occurred). The status of the attributeprofiles of the components and the pie product are, therefore, known byway of the monitoring devices 711, 713, 715 and 717. In an optionalembodiment, the updated attribute profile status is input to dataprocessing apparatus 728 which is configured to be responsive to theupdated status to deduce an updated component ratio and forward theratio to control unit 729. The control unit 729 then sends controlsignals to the relevant valves 719, 721 and/or 723 to adjust thedispensation of components to the conveyor belt 709.

Following a change or predicted change (based on acquired information725) in a component attribute profile, for example the reducedavailability of vegetables A, the change is included in information 725and supplied to the database 727. The data processor 728 accesses theinformation 725 in the database 727 and establishes whether the changeor predicted change will result in an unacceptable deviation from thetarget product attribute profile. If such a deviation is identified, thedata processor 728 deduces how best to counteract the deviation bygenerating an updated component ratio which more closely yields thetarget product attribute profile.

The data processor 728 can establish that a deviation is likely to occurdue to the reduced availability of sugar. In this particular case, thedata processor algorithm generates a solution to this problem; moreparticularly an adjusted ratio/combination of the components which wouldminimise the deviation owing to the reduced availability of vegetablesA. In this embodiment, the data processor 728 calculates that thevegetables A of vessel 705 can be replaced by vegetables B of vessel 707due to similar component attributes, whereby to minimise the deviationof the target and current product attribute profiles.

Using the calculated adjustment, an operator can manipulate the controlunit 729 to make said adjustment to the combination in conveyor belt 709by closing dispenser 721, belonging to vessel 705, and opening dispenser723, belonging to vessel 707. The adjustment is made by effectivelyreplacing vegetables A with vegetables B. Of course, in otherembodiments, a component may not be entirely replaced; instead theamount supplied of a particular component may change. Optionally, theadjustment may be made automatically in that updated control parametersto modify the product component ratio/amount input to the conveyor belt709 are sent to the control unit 729. The control unit 729 may then sendcontrol signals to valves 719, 721 and 723 to adjust the dispensation ofcomponents to incorporate vegetable B from vessel 707.

Following said adjustments, resulting pie 734 comprising chicken andvegetables B may be taken off the conveyor belt 709.

In this embodiment, the pie pastry 724 moves along the conveyor belt 709in the direction indicated by arrow 726. The pie pastry, alsoconstituting a component of the product, is filled with other componentsincluding chicken and vegetables A or B along its travel. The pieproduct 734 comprises components of the pie pastry, chicken, andvegetables B (following adjustment).

Referring now to FIGS. 8 and 9, there is depicted a two dimensionallinear integer program and a graphical representation of an interiorpoint method model, respectively. More particularly, FIG. 8 shows theparent relaxed problem and the first two sub-problems from branching onvariable X(i).

The objective function 801 and constraints 803 combine to form a mathprogram. The solution method optimizes the objective function subject tothe constraints 803. In this embodiment, a branch and bound algorithm isused to solve the math program. The integer requirements are relaxed andthe math program is solved as a continuous variable problem. Thisrelaxed problem can be solved using an interior point algorithm, or agradient descent algorithm. A variable is selected to ‘branch’ on basedon the partial derivative of the objective function, projected onto theconstraint surface, with respect to the variable. Along one branch thebranching variable is constrained to be less than or equal to the nextlowest integer value 805, while along the other branch the branchingvariable is constrained to be greater than or equal to the next highestvalue (see FIG. 8). The resulting sub-problems are solved until anoptimal solution 807 is found that obeys all constraints and integralityrequirements.

As can be seen from FIG. 9, the optimal feasible solution 807 is thatpoint which is within the bounds but maximizes the objective function801. Although, the integer point 805 to the bottom right of the optimalinteger point 807 may provide greater attribute function in somerespects, this integer point 805 falls outside the constraint 803 boundsset and thus cannot be considered the optimal solution 807.

In other embodiments, a branch and cut algorithm may be used, and branchand bound and branch and cut can be used in combination.

It is to be understood that any feature described in relation to any oneembodiment may be used alone, or in combination with other featuresdescribed, and may also be used in combination with one or more featuresof any other of the embodiments, or in combination of any of theembodiments.

Insofar as embodiments of the invention described are implementable, atleast in part, using a software-controlled programmable processingdevice such as a general purpose processor or special-purposesprocessor, digital signal processor, microprocessor, or other processingdevice, data processing apparatus or computer system it will beappreciated that a computer program for configuring a programmabledevice, apparatus or system to implement the foregoing describedmethods, apparatus and system to implement the foregoing describedmethods, apparatus and system is envisaged as an aspect of the presentinvention. The computer program may be embodied as any suitable type ofcode, such as a source code, object code, compiled code, interpretedcode, executable code, static code, dynamic code, and the like. Theinstructions may be implemented using any suitable high-level,low-level, object-oriented, visual, compiled and/or interpretedprogramming language, such as C, C++, Java, BASIC, Perl, Matlab, Pascal,Visual BASIC, JAVA, Active X, assembly language, machine code, and soforth. A skilled person would readily understand the term “computer” inits most general sense encompasses programmable devices such as referredto above, and data processing apparatus and computer systems.

Suitably, the computer program is stored on a carrier medium in machinereadable form, for example the carrier medium may comprise memory,removable or non-removable media, erasable or non-erasable media,writable or re-writable media, digital or analogue media, hard disk,floppy disk. Compact Disk Read Only Memory (CD-ROM), Compact DiskRecordable (CD-R), Compact Disk Rewritable (CD-RW), optical disk,magnetic media, magneto-optical media, removable memory cards or disks,various types of Digital Versatile Disk (DVD) subscriber identifymodule, tape, and cassette solid-state memory. The computer program maybe supplied from a remote source embodied in the communications mediumsuch as an electronic signal, radio frequency carrier wave or opticalcarrier waves. Such carrier media are also envisaged aspects of thepresent invention.

As used herein, the terms “comprises”, “comprising”, “includes”,“including”, “has”, “having” or any other variation thereof, areintended to cover a non-exclusive inclusion. For example, a process,method, article, or apparatus that comprises a list of elements is notnecessarily listed or inherent to such process, method, article, orapparatus. Further, unless expressly stated to the contrary, “or” refersto an inclusive or and not to an exclusive or. For example, a conditionA or B is satisfied by any one of the following: A is true (or present)and B is false (or not present), A is false (or not present) and B istrue (or present), and both A and B are true (or present).

In addition, use of the “a” or “an” are employed to describe elementsand components of the invention. This is done merely for convenience andto give a general sense of the invention. This description should beread to include one or at least one and the singular also includes theplural unless it is obvious that it is meant otherwise.

The scope of the present disclosure includes any novel feature orcombination of features disclosed therein either explicitly orimplicitly or any generalisation thereof irrespective of whether or notit relates to the claimed invention or mitigate against any or all ofthe problems addressed by the present invention. The applicant herebygives notice that new claims may be formulated to such features duringprosecution of this application or any such further application derivedtherefrom. In particular, with reference to the appended claims, featurefrom dependent claims may be combined with those of the independentclaims and features from respective independent claims may be combinedin any appropriate manner and not merely in specific combinationsenumerated in the claims.

1. A method of producing a multi-component product comprising a productattribute profile, the method comprising providing a first and secondcomponent of the product, each component having a component attributeprofile; supplying to a product formulation zone the first component andthe second component in desired amounts and combining the first andsecond components together to provide the product or a precursor thereofto yield a target product attribute profile; responsive to a change orpredicted change in at least one component attribute profile, supplyinginformation concerning the attribute change to a data processingapparatus and calculating with respect to that change an adjustment inthe amounts to reduce the deviation of one or more attributes of theproduct attribute profile from the target product attribute profile. 2.The method of claim 1, further comprising storing said information in adatabase and supplying said information to said data processingapparatus from said database.
 3. The method of claim 1 or 2, furthercomprising monitoring the attribute profile of each of the first andsecond components.
 4. The method of any of claims 1 to 3, furthercomprising monitoring the product attribute profile and responsive to achange or predicted change in an attribute of said product attributeprofile supplying further information concerning said change to saiddata processing apparatus for use in calculating said adjustment.
 5. Themethod of any of claims 1 to 4, wherein the first and second componentsreside in separate vessels before being combined.
 6. The method of claim5, wherein the vessels include valves for allowing controlled passage ofthe components to the product formulation zone.
 7. The method of any ofclaims 1 to 6, wherein the at least one component attribute profile isselected from the cost of freight and storage of a particular component,cost of a particular component, quality of a particular component,consumer demand of a particular component, available supply of aparticular component, and cost of processing.
 8. The method of any ofclaims 1 to 7, wherein the method is a computer implemented method andthe calculating step executed by a data processor.
 9. A system forproducing a multi-component product comprising a product attributeprofile, the system comprising means for storing a first and secondcomponent of the product, a product formulation zone for combining thefirst and second component of the product in desired amounts effectiveto yield a target product attribute profile, the first and secondcomponent each having a component attribute profile, wherein the systemcomprises a data processing apparatus operable to receive informationconcerning a change or predicted change in at least one componentattribute profile and, in response thereto, is operable to calculatewith respect to that change an adjustment in the amounts to reduce thedeviation of one or more attributes of the product attribute profilefrom the target product attribute profile.
 10. The system of claim 9,wherein an attribute of at least one component of the product fluctuatesover time.
 11. The system of claim 9 or claim 10, further comprisingmeans for adjusting the component amounts.
 12. The system of any ofclaims 9 to 11, wherein the means for storing the first and secondcomponents comprises separate vessels.
 13. The system of any of claims 9to 12, wherein the formulation zone comprises a combination chamber. 14.The system of any of claims 9 to 13, further comprising a database forstoring said information.
 15. The system of any of claims 9 to 14,further comprising at least one monitoring device for monitoring theattribute profile of each of the first and second components.
 16. Use ofthe system according to any of claims 9 to 15 in regulating amulti-component product attribute profile.
 17. A computer programcomprising computer program elements operative in data processingapparatus to implement the method of any of claims 1 to 8 or system ofany of claims 9 to
 15. 18. A computer implementable method of modellingthe production of a multi-component product comprising: representingsaid multi-component product by data values indicative of a physicalattribute profile of said multi-component product; representing firstand second components of said multi-component product by data valuesindicative of respective physical attributes of said first and secondcomponents; and deriving a combinatorial relationship between respectivedata values of said physical attributes of said first and secondcomponent to yield a combined attribute profile within predeterminedlimits of data values of said multi-component product attribute profile.19. A method according to claim 18, wherein said constraint comprises afurther data value or range of data values representative of anavailable amount of said first and/or second component.
 20. A methodaccording to claim 18 or claim 19, wherein said constraint comprises ayet further data value or range of data values representative of anamount of multi-component product to be produced.
 21. A method accordingto any of claims 18 to 20, wherein said combinational relationshipcomprises a ratio of said first component to said second component. 22.A method according to any of claims 18 to 21, further comprisingproviding control parameters derived from said combined attributeprofile to a multi-component production system for controlling thesupply of said first and second component to a formulation zone inamounts corresponding to said combinatorial relationship for combiningto form said multi-component product.
 23. A computer program comprisingcomputer program elements operative in data processing apparatus toimplement the method of any of claims 18 to 22.